GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation
In this study, we demonstrate an application for 5G networks in mobile and remote GPR scanning situations to detect buried objects by experts while the operator is performing the scans. Using a GSSI SIR-30 system in conjunction with the RealSense camera for visual mapping of the surveyed area, subsu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/12/6552 |
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| author | Scott Tanch Alireza Fath Nicholas Hanna Tian Xia Dryver Huston |
| author_facet | Scott Tanch Alireza Fath Nicholas Hanna Tian Xia Dryver Huston |
| author_sort | Scott Tanch |
| collection | DOAJ |
| description | In this study, we demonstrate an application for 5G networks in mobile and remote GPR scanning situations to detect buried objects by experts while the operator is performing the scans. Using a GSSI SIR-30 system in conjunction with the RealSense camera for visual mapping of the surveyed area, subsurface GPR scans were created and transmitted for remote processing. Using mobile networks, the raw B-scan files were transmitted at a sufficient rate, a maximum of 0.034 ms mean latency, to enable near real-time edge processing. The performance of 5G networks in handling the data transmission for the GPR scans and edge computing was compared to the performance of 4G networks. In addition, long-range low-power devices, namely Wi-Fi HaLow and Wi-Fi hotspots, were compared as local alternatives to cellular networks. Augmented reality headset representation of the F-scans is proposed as a method of assisting the operator in using the edge-processed scans. These promising results bode well for the potential of remote processing of GPR data in augmented reality applications. |
| format | Article |
| id | doaj-art-ead1a06fef3b45ef81365f6fc2e6cf9c |
| institution | Matheson Library |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-ead1a06fef3b45ef81365f6fc2e6cf9c2025-06-25T13:25:13ZengMDPI AGApplied Sciences2076-34172025-06-011512655210.3390/app15126552GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR RepresentationScott Tanch0Alireza Fath1Nicholas Hanna2Tian Xia3Dryver Huston4Mechanical Engineering, University of Vermont, Burlington, VT 05405, USAMechanical Engineering, University of Vermont, Burlington, VT 05405, USAComputer Science, University of Vermont, Burlington, VT 05405, USAElectrical and Biomedical Engineering, University of Vermont, Burlington, VT 05405, USAMechanical Engineering, University of Vermont, Burlington, VT 05405, USAIn this study, we demonstrate an application for 5G networks in mobile and remote GPR scanning situations to detect buried objects by experts while the operator is performing the scans. Using a GSSI SIR-30 system in conjunction with the RealSense camera for visual mapping of the surveyed area, subsurface GPR scans were created and transmitted for remote processing. Using mobile networks, the raw B-scan files were transmitted at a sufficient rate, a maximum of 0.034 ms mean latency, to enable near real-time edge processing. The performance of 5G networks in handling the data transmission for the GPR scans and edge computing was compared to the performance of 4G networks. In addition, long-range low-power devices, namely Wi-Fi HaLow and Wi-Fi hotspots, were compared as local alternatives to cellular networks. Augmented reality headset representation of the F-scans is proposed as a method of assisting the operator in using the edge-processed scans. These promising results bode well for the potential of remote processing of GPR data in augmented reality applications.https://www.mdpi.com/2076-3417/15/12/6552GPRedge computing5G networkvisual mapping4G networkimage processing |
| spellingShingle | Scott Tanch Alireza Fath Nicholas Hanna Tian Xia Dryver Huston GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation Applied Sciences GPR edge computing 5G network visual mapping 4G network image processing |
| title | GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation |
| title_full | GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation |
| title_fullStr | GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation |
| title_full_unstemmed | GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation |
| title_short | GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation |
| title_sort | gpr sensing and visual mapping through 4g lte 5g wi fi halow and wi fi hotspots with edge computing and ar representation |
| topic | GPR edge computing 5G network visual mapping 4G network image processing |
| url | https://www.mdpi.com/2076-3417/15/12/6552 |
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